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storehausai

ECOUNT MCP Server

by storehausai

ecount_create_quotation

Create and register ECOUNT quotations. Specify product code, customer, quantity, price, and more to generate quotation slips, with items sharing an upload serial number forming one quotation.

Instructions

견적서 입력. 고객에게 제시할 견적서를 ECOUNT에 등록합니다. 각 항목에 품목코드(PROD_CD)는 필수이며, 거래처/수량/단가/금액 등을 입력합니다. UPLOAD_SER_NO가 같은 항목들은 하나의 견적서로 묶입니다. 최대 300건까지 등록 가능. [Rate Limit: 10초/1회] [Response: success(성공건수), failed(실패건수), slipNos(전표번호 배열 - YYYYMMDD-N 형식), details(상세결과 - IsSuccess, TotalError, Errors 배열)]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes견적 품목 목록. 1~300건. UPLOAD_SER_NO가 같은 항목들은 하나의 견적서로 묶임
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses key behaviors: items with the same UPLOAD_SER_NO group into one quotation, a maximum of 300 items, a rate limit of one request per 10 seconds, and the response format including success/failure counts and slip numbers. It does not cover authorization or reversibility, but the disclosed details are substantial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured, starting with the main purpose, followed by requirements, grouping, limits, and clearly bracketed meta info (rate limit and response). Every sentence adds meaningful information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of an array-based creation tool with many optional fields, the description explains the grouping mechanism, maximum items, rate limit, and response structure. The schema covers parameter semantics, so the description is sufficiently complete for correct invocation, though it does not mention potential error handling beyond the response details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, with all parameters described in the schema. The description adds only a high-level mention of required PROD_CD and grouping logic, both already present in the schema. Thus, the description adds minimal value beyond the schema, but the schema is fully descriptive.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool registers quotations (견적서) for customers in ECOUNT, using a specific verb '등록합니다' and resource '견적서'. It distinguishes from sibling tools by emphasizing customer-facing quotation presentation rather than sales orders or other document types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context that this tool is for entering quotations to present to customers, implying its use for quotation creation. However, it does not explicitly name alternative tools or state when not to use it, so it lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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